The present invention relates to a system and method for data collection, evaluation, information generation, and presentation. More particularly the present invention relates to a system for collecting, evaluating, and presenting data, and generating information relating to electronic commerce. The system and methods of the present invention include one or more of the following: a module for stabilizing small or noisy samples of data; alarm modules that alert an event handler when data values cross specified thresholds; predictor modules that use recent historical data along with an estimated and/or available saturation population function as the basis for a differential equation that defines the growth of the population to a maximum attainable level; and a dynamic icon that conveys to users of a system levels of predefined activity occurring on the system.
The availability of relatively low cost, powerful computer systems and the development of online communication systems and networksxe2x80x94principally the Internet and its protocols, and the availability of low-cost consumer computer systemsxe2x80x94have fueled the growth of e-commerce. As used herein xe2x80x9ce-commercexe2x80x9d means commercial transactions for goods or services, particularly wholesale or retail sales of products or services, or bartered exchange of the foregoing, over global computer networks, such as the Internet, or any smaller computer network that unites users and suppliers of goods or services.
The rapid growth of e-commerce makes the need for such guidance even more compelling. In a study by the assignee of the present invention, it was found that over the 12-month period ending June 1999, total retail e-commerce sales tripled from $2.67 to $7.94 billion. (Source: 2ND QTR: 1999 Consumer Online Report for Total Retail e-commerce, published by BizRate.com, 1999).
The Internet has been swiftly facilitating the growth of local and regional markets into national and international markets. This market expansion provides consumers with many new advantages and opportunities including better product pricing, product selection, product quality, and customer service. The market expansion also creates new advantages and opportunities for businesses, including a broader base of consumers and suppliers. With the advantages and opportunities come new challenges.
The success of a business engaged in e-commerce may depend on how well it understands the dynamics and parameters of the e-commerce marketplace, and how well the business understands its status in such marketplace. Unfortunately, traditional models for evaluating the performance of a business are not well suited or optimized for evaluating the performances of businesses engaged in e-commerce. The nature of e-commerce and the manner in which it is conducted demand new and improved systems and methods for evaluating business performance. Consumers also need guidance so that they may understand their options and make the best decisions when doing business online.
From the consumer perspective, chief among the challenges is finding among the myriad of online businesses the merchants who offer the category of products sought at the best pricing, product selection, product quality, reputation, etc. The rating of a merchant relative to such variables may change rapidly in response to marketplace conditions. For example, marketplace competition may drive competitors to change their prices daily. Product availability may also change on as frequent a basis. For such reasons, consumers need a mechanism that helps them quickly locate the best merchants for their needs based on the most current and accurate data and information available.
Merchants also face new challenges in the online marketplace. They must be able to reach consumers and communicate to consumers the value they can deliver. To do this, they must understand the competition, and what drives consumers to make purchases. They must monitor their own prices relative to competitors"" prices on a frequent basis to remain competitive. They must also understand what level of satisfaction or dissatisfaction consumers have from transactions with themselves and competitors, as well as the bases of satisfaction or dissatisfaction. For such reasons, merchants need a mechanism that helps them quickly obtain the most current and accurate information.
Traditionally, marketing surveys have been employed to determine how well a business rates in the eyes of consumers. Direct feedback from consumers provides important information. In traditional forms of commerce, consumer satisfaction surveys have been long used to gather direct feedback from consumers. (Traditional forms of commerce include in-store, telephonic, and mail order commerce.) The surveys help businesses understand what positive and negative things they a re doing. With the proper understanding, the businesses may reinforce the positive things and correct the negative ones. The more accurate and current the survey results, the better a business can achieve its objectives.
Unfortunately, administering and processing consumer surveys, even in traditional modes of commerce, has been problematic in various respects, for example:
How do you get consumers to fill out such surveys?
Is the sample size of responses large enough to produce accurate reports?
How do you input and process the data?
Has the data been processed in a timely manner?
How are results to be timely reported to businesses?
What do the results mean to the business?
What steps should the business take in view of the results?
What has bee n the effect of any remedial action?
With respect to these questions, there are many problems. The surveys are typically presented to consumers as paper questionnaires for the consumers to manually fill in. Such surveys may be costly to construct and print. Once printed, they cannot be modified. Consumers generally dislike filling out survey questionnaires, and therefore it may be difficult or time consuming for the survey sponsor to gather enough completed survey questionnaires to constitute a statistically significant sample size. Often, the completed survey questionnaires must be returned by mail; even if a consumer has filled out the survey questionnaire, the consumer may not take the trouble of dropping it in the mailbox.
To over come these kinds of problems, survey sponsors sometimes employ individuals to field survey responses from individuals. These individuals may be stationed in a store to verbally field answers to survey questions or they may telephone consumers after a transaction. The problem with using individuals to administer surveys is the cost of administering the survey and the intrusiveness of the process. The intrusiveness is such that consumers may be alienated from doing further business with a merchant. This is particularly a concern relative to telephone surveys. With intrusive survey methods, even if the consumer is inclined to answer questions by a survey taker, the consumer""s answers may be skewed toward an unfavorable response, creating inaccurate results.
The processing of completed survey questionnaires has its own set of disadvantages. The completed survey questionnaires usually must be read by data entry personnel and manually input by them into a data processing system. This not only adds to the cost of administering a survey, but it also results in delays between the time surveys are taken and the time the results are processed.
In view of the inherent delays in administering surveys and inputting survey data, by the time a business receives a report of the results of a survey, the results may no longer be accurate. For example, consider a survey about price competitiveness: competitors may have dropped prices in the interval between the responses to a survey and the processing and reporting of information. During such an interval, a business could lose significant sales and revenues because they have not reacted contemporaneously to competitors"" price changes. If there is a decline in consumer service ratings that is not corrected quickly because of the interval between survey responses and reporting of results, a business may also lose consumer goodwill, and consequently sales and revenues.
Another problem with traditional survey modes is that a business may have difficulty benefiting from the survey results. One reason is that, although a business can take remedial action in view of the results, to monitor the results of any remedial action requires a subsequent survey. There is a disincentive for a subsequent survey because of all the aforementioned disadvantages related to traditional modes of surveying such as cost, time required, etc. However, if the problems inherent in traditional forms of surveying could be overcome, subsequent surveys could be undertaken to determine the effectiveness of remedial action dictated by the initial survey.
In view of the disadvantages in traditional survey methodology, a few years ago the assignee of the present invention developed and implemented a novel system for providing timely and accurate reporting of information relating to the sales, marketing, consumer satisfaction, and other commercial activities of participating businesses. In the system, online buyers are non-intrusively invited to fill out a survey questionnaire immediately after completing a purchase at a participating merchant. The invitation is in the form of a banner on the order confirmation receipt from a participating merchant""s website. If the buyer has clicked on the banner to accept the survey questionnaire, the buyer is hyper-linked to a questionnaire from a survey system server. The buyer completes the survey questionnaire and the survey data are electronically returned to a data processing system for processing and evaluating survey results. The same system can electronically report the processed results from a sample of survey questionnaires directly to participating or subscribing merchants.
Thus, the system of the assignee overcomes disadvantages in the art by providing a system that electronically gathers data and transmits it directly into the data processing system. Among the advantages of this system, it eliminates the need for manual entry of data on paper forms; the use of individuals to take and input survey data gathered from consumers; the delays that occur between data collection and input, and data input and processing; and the costs associated with such methodologies. While this system has begun to address many disadvantages of traditional modes of surveying, processing, and evaluating survey data, the dynamics of the e-commerce marketplace demand faster and more accurate data gathering, processing, evaluation and reporting of data and information.
The rate at which reports can be issued depends on how fast survey responses are returned and on the minimum sample size required. It is fundamental in statistical sciences that, when conventional modes of statistical analysis are employed, an inadequately small sample or a noisy sample will lead to inaccurate results. However, business and marketplace conditions may be changing faster than adequate sample sizes can be gathered for accurate results using conventional modes of statistical analysis and estimation theory. Such conventional modes include xe2x80x9cmoving window averagesxe2x80x9d (weighted and unweighted). Accordingly, businesses may be at risk if certain trends relating to the business or marketplace take shape before data is collected in sample sizes suitable for traditional modes of statistical analysis and estimation.
In view of the foregoing, there is a strong need for novel data processing systems that can discern trends and otherwise provide results based on limited or noisy data samples. Further in view of the foregoing, there is a substantial need for data gathering, processing and evaluation systems that quickly alert businesses to incipient trends in their business activities and marketplace so that appropriate action may be taken to protect and advance a business""s well-being. There is also a need for systems that allow a business to predict growth rates and limits of variables relating to the business or marketplace.
The present invention relates to a system and method for data collection, information generation, evaluation, and presentation that overcomes the aforementioned problems in the prior art. More particularly the present invention relates to a system for collecting data, generating, evaluating, and presenting information relating to electronic commerce via the Internet. The system and methods of the present invention include one or more of the following: a module for stabilizing small or noisy samples of data; alarm modules that alert a handler when data values are anomalous or cross specified thresholds; predictor modules that use recent historical data along with an estimated and/or available saturation population function as the basis for a differential equation that predicts the future growth of the population to a maximum attainable level; and a dynamic measurement indicator that conveys to users of a system levels of predefined and ongoing activity occurring on another system. The fields of the invention include ecommerce; information retrieval/analysis; and planning and control. Before the present invention, the period for gathering sufficient quantities of data to resolve a trend often exceeded the time required for a merchant to begin suffering lost sales or other harms because of an undetected incipient trend.
In one novel embodiment, the present invention provides a system for forecasting population values comprising one or more databases containing data for processing; a plurality of processing modules in communication with each other and/or the one or more databases, each processing module performing a predefined operation on data stored in a database or received from a processing module, at least one processing module being a saturation limited forecasting (xe2x80x9cSLFxe2x80x9d) module for forecasting the value of a population for a given time; one or more databases in communication with the SLF processing module for storing data that has been processed through the SLF processing module; and a presentation server in communication with a database with the processed data for presenting selected items of data. Data on the presentation server may be accessible to a plurality of remote computer systems via the Internet. The system may further include a data capture server in communication one or more data sources over the Internet, the data capture server providing data to the one or more databases. The system may also include a survey server that serves a survey questionnaire to one or more remote computer systems comprising data sources so that a user of a remote computer system comprising a data source can complete the survey questionnaire, a completed survey questionnaire being returnable to the data capture server over the Internet. The remote computer systems may be a plurality of consumer computer systems, and completed survey questionnaires may include data relating to an online transaction between a consumer and a merchant. The remote computer systems may also be a plurality of merchant computer systems. The presentation server may serve ratings about online merchants, the ratings being based on data collected from consumer computer systems. In the system, the SLF processing module may use available recent historical data along with an estimated and/or available saturation population function as the basis for a differential equation that defines the growth of a population to a maximum attainable level. The SLF module may use a pull function P0(t) which sets a population""s saturation limit to growth and a penetration function r(t) which characterizes the total level of effort process, the SLF forecasting the value of a population for a given time. The SLF module may use a growth differential equation             ⅆ      P              ⅆ      t        =            r      ⁢              (        t        )              ⁡          [                                    P            0                    ⁢                      (            t            )                          -                  P          ⁢                      (            t            )                              ]      
to arrive at forecasted population value for a given time. The SLF module may use an equation             c      _        *    =      arg    ⁢          xe2x80x83        ⁢                  min                              xe2x80x83                    ⁢                      c            _                    ⁢                      xe2x80x83                              ⁢              {                              ∑                          i              =              1                        N                    ⁢                                    (                                                P                  i                                -                                                      [                                                                  ∫                                                  t                          0                                                                          t                          F                                                                    ⁢                                                                                                    r                            ⁡                                                          (                                                                                                c                                  _                                                                ,                                t                                                            )                                                                                ⁡                                                      [                                                                                                                            P                                  0                                                                ⁡                                                                  (                                  t                                  )                                                                                            -                                                              P                                ⁡                                                                  (                                  t                                  )                                                                                                                      ]                                                                          ⁢                                                  ⅆ                          t                                                                                      ]                                                        t                    i                                                              )                        2                          }            
to arrive at a forecasted population value for a given time. In the system, the presentation server may include web pages containing data or information relating to a forecasted e-commerce population, the data or information being derived from an SLF processing module.
In another novel embodiment, the present invention provides a system for forecasting population values comprising a data capture server capable of communicating with one or more data sources over a computer network, a data source providing data related to e-commerce; one or more databases for receiving data from the data capture server; a plurality of processing modules in communication with each other and/or the one or more databases, each processing module performing a predefined operation on data stored in a database or received from a processing module, one processing module comprising a saturation limited forecasting (xe2x80x9cSLFxe2x80x9d) module and one processing module comprising a statistical analysis processing module in communication with the SLF module, the SLF module being adapted to forecast population values for a given time; one or more databases in communication with the one or more processing modules for storing data received from a selected processing module; and a presentation server in communication with one or more of the databases, the presentation server being capable of accessing the data passed through the SLF module and presenting selected items of data as data or information, the presentation server being accessible to remote computer systems via a network. The one or more data sources include consumer and/or merchant computer systems, and the presentation server is capable of communicating with one or more merchant computer systems to communicate processed data relating to transactions between consumers and merchants, the processed data originating as raw data from consumer computer systems.
In another novel embodiment, the present invention provides a presentation server that includes files containing data or information relating to a forecasted e-commerce population, the data or information being derived from an SLF processing module.
In another novel embodiment, the present invention provides a presentation server that includes web pages containing data or information relating to a forecasted e-commerce population, the data or information being derived from an SLF processing module, the web pages being accessible to a plurality of remote consumer computer systems over a computer network, such as the Internet. In the presentation servers of the present invention, data input to the SLF processing module is processed using a pull function P0(t) which sets a population""s saturation limit to growth and a penetration function r(t) which characterizes the total level of effort process, the SLF forecasting the value of a population for a given time. In the presentation servers of the present invention, the SLF module may use a growth differential equation             ⅆ      P              ⅆ      t        =            r      ⁢              (        t        )              ⁡          [                                    P            0                    ⁢                      (            t            )                          -                  P          ⁢                      (            t            )                              ]      
to arrive at forecasted population value for a given time. In the presentation servers of the present invention, the SLF module may use an equation             c      _        *    =      arg    ⁢          xe2x80x83        ⁢                  min                              xe2x80x83                    ⁢                      c            _                    ⁢                      xe2x80x83                              ⁢              {                              ∑                          i              =              1                        N                    ⁢                                    (                                                P                  i                                -                                                      [                                                                  ∫                                                  t                          0                                                                          t                          F                                                                    ⁢                                                                                                    r                            ⁡                                                          (                                                                                                c                                  _                                                                ,                                t                                                            )                                                                                ⁡                                                      [                                                                                                                            P                                  0                                                                ⁡                                                                  (                                  t                                  )                                                                                            -                                                              P                                ⁡                                                                  (                                  t                                  )                                                                                                                      ]                                                                          ⁢                                                  ⅆ                          t                                                                                      ]                                                        t                    i                                                              )                        2                          }            
to arrive at a forecasted population value for a given time.
In another novel embodiment, the present invention provides a method of presenting data or information relating to a forecasted e-commerce population, comprising providing a presentation server that includes files containing data or information relating to a forecasted e-commerce population, and making the web pages being accessible to a plurality of remote consumer computer systems over a computer network, such as the Internet. Data input to the SLF processing module may be processed using a pull function P0(t) which sets a population""s saturation limit to growth and a penetration function r(t) which characterizes the total level of effort process, the SLF forecasting the value of a population for a given time. The SLF processing module may use a growth differential equation             ⅆ      P              ⅆ      t        =            r      ⁢              (        t        )              ⁡          [                                    P            0                    ⁢                      (            t            )                          -                  P          ⁢                      (            t            )                              ]      
to arrive at forecasted population value for a given time. The SLF module may use an equation             c      _        *    =      arg    ⁢          xe2x80x83        ⁢                  min                              xe2x80x83                    ⁢                      c            _                    ⁢                      xe2x80x83                              ⁢              {                              ∑                          i              =              1                        N                    ⁢                                    (                                                P                  i                                -                                                      [                                                                  ∫                                                  t                          0                                                                          t                          F                                                                    ⁢                                                                                                    r                            ⁡                                                          (                                                                                                c                                  _                                                                ,                                t                                                            )                                                                                ⁡                                                      [                                                                                                                            P                                  0                                                                ⁡                                                                  (                                  t                                  )                                                                                            -                                                              P                                ⁡                                                                  (                                  t                                  )                                                                                                                      ]                                                                          ⁢                                                  ⅆ                          t                                                                                      ]                                                        t                    i                                                              )                        2                          }            
to arrive at a forecasted population value for a given time. The method may further include capturing data in a data capture server and then transferring captured data for input into the SLF processing module. The data may be captured from survey questionnaires. The survey questionnaires may be completed by consumers and delivered to a data capture server over the Internet.
The foregoing enumeration of embodiments has been for illustrative purposes only. Other embodiments, combinations of embodiments and combination of features are also within the scope and sprit of the teachings described herein, as will be apparent to persons skilled in the art from these teachings.